不同视觉辅助刺激下运动想象大脑皮层因果连接网络特性分析  

Analysis of MI Brain Causal Networks Under Different Visual Stimuli Guidance

作　　者：边琰 赵丽 傅星[1] 綦宏志[1] Bian Yan;Zhao Li;Fu Xing;Qi Hongzhi(School of Precision Instrument and Opto-Electronics Engineering,Tianjin University,Tianjin 300072,China;Tianjin Information Sensing&Intelligent Control Key Lab,Tianjin University of Technology and Education,Tianjin 300222,China)

机构地区：[1]天津大学精密仪器与光电子工程学院,天津300072 [2]天津市信息传感与智能控制重点实验室,天津300222

出　　处：《中国生物医学工程学报》2020年第6期685-692,共8页Chinese Journal of Biomedical Engineering

基　　金：国家自然科学基金(81630051,91648122)。

摘　　要：基于运动想象(MI)的脑-机接口系统(BCI)被认为是一种很有潜力的运动功能康复方法,但是经典MIBCI使用时存在个体差异性大、识别率较低的问题。采用视觉辅助刺激范式可以增强MI特征,并能有效提高BCI识别的准确率。然而在不同的视觉辅助刺激范式下,MI任务期的大脑皮层因果连接响应特征及其面向运动功能康复的神经生理学意义却鲜有报道。设计4种不同类型的视觉辅助刺激范式,包括不同的动态/非动态视觉刺激及简单/复杂想象任务范式,选取MI任务期大脑运动感觉相关皮层7个感兴趣区域,利用孤立有效相干法(iCoh),对11名被试beta频段4种实验范式构建单尾单样本t检验(P<0.01)平均因果脑网络,并分析网络的平均度分布、聚类系数、全局效率、中介中心度参数。结果表明,相比于简单想象任务非动态视觉刺激范式,复杂想象任务动态视觉刺激范式平均度分布由2.143提高为2.429,聚类系数由0.634提高为0.767,全局效率由0.393提高为0.417。复杂想象任务动态刺激范式下,辅助运动皮层和顶上小叶、顶下小叶存在因果连接关系,辅助运动皮层成为脑网络中的关键节点。Brain-computer interface(BCI) based on motor imagery(MI) is believed to be a potential approach for motor rehabilitation.However,classical MI-BCI leaves the questions of large individual differences and low recognition accuracy.By making use of visual stimuli guidance could enhance MI features and improve BCI recognition accuracy.Nevertheless,rare attention has been paid to the features of brain causal networks during MI under different visual stimuli paradigms and their impacts on motor recovery.We designed four different types of visual stimuli guidance in this paper,including dynamic/non-dynamic stimuli and simple/complex MI tasks.The beta one-tailed one-sample t test(P < 0.01) causal significant connectivity networks of seven regions of interest located in motor-sensory cortex were built based on isolated effective coherence(iCoh)during MI,and parameters of degree distribution,clustering coefficient,global efficiency and betweenness centrality were further analyzed.The outcomes showed that compared with non-dynamic and simple MI task experimental paradigm,the average degree distribution of dynamic visual paradigms combined with complex MI task was varied from 2.143 to 2.429;the clustering coefficient was varied from 0.643 to 0.767;the global efficiencie was varied from 0.393 to 0.417.Under dynamic with complex task paradigms,the significant connectivity exist between SMA and SPL,IPL,thus SMA becomes the key node in the brain causal networks.

关 键 词：脑-机接口 运动想象 视觉刺激 脑网络 孤立有效相干法 

分 类 号：R318[医药卫生—生物医学工程]